fmri: biological basis and experiment design lecture 24: glm in all its glory

fMRI: Biological Basis and Experiment DesignLecture 24: GLM in all its glory

Previously ...

X =

time

Assumed shape of HIRF, analysis for single voxel

Previously ...

X =

time

voxels

voxels

Assumed shape of HIRF, analysis in many voxels

Today

x =

time

Estimate shape of HIRF (single voxel)

Design matrix

time

stim 1 stim 2 stim 3 baseline trends, etc.stim

1stim

2stim

3

Assuming HIRF: Not assuming HIRF:

Regression coefficients

stim 1

Assuming HIRF: Not assuming HIRF:

stim 2

stim 3

trend 1

trend 2

trend 3

stim 1

stim 2

stim 3

trends

Example 1: Slow ER, "same" HIRFs, no trends

no trends

A x

Data simulation: A*x + noise

Example 1: Slow ER, "same" HIRFs, no trends

Example 1: Slow ER, "same" HIRFs, no trends

Example 2: Slow ER, "same" HIRFs, trends

Example 2: Slow ER, "same" HIRFs, trends

Example 3: Rapid ER, "same" HIRFs, no trends

Example 3: Rapid ER, "same" HIRFs, no trends

Example 4: Rapid ER, diff. HIRFs, no trends

Example 4: Rapid ER, diff. HIRFs, no trends

Example 5: Rapid ER, diff. HIRFs, trends

Example 5: Rapid ER, diff. HIRFs, trends

Example 6: Block design, diff. HIRFs, trends

Example 6: Block design, diff. HIRFs, trends